Instructions to use ragbox/bge-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ragbox/bge-reranker with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ragbox/bge-reranker", filename="Bge-Reranker-v2-M3-568M-Q8_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use ragbox/bge-reranker with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ragbox/bge-reranker:Q8_0 # Run inference directly in the terminal: llama-cli -hf ragbox/bge-reranker:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ragbox/bge-reranker:Q8_0 # Run inference directly in the terminal: llama-cli -hf ragbox/bge-reranker:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf ragbox/bge-reranker:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ragbox/bge-reranker:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf ragbox/bge-reranker:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ragbox/bge-reranker:Q8_0
Use Docker
docker model run hf.co/ragbox/bge-reranker:Q8_0
- LM Studio
- Jan
- Ollama
How to use ragbox/bge-reranker with Ollama:
ollama run hf.co/ragbox/bge-reranker:Q8_0
- Unsloth Studio new
How to use ragbox/bge-reranker with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ragbox/bge-reranker to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ragbox/bge-reranker to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ragbox/bge-reranker to start chatting
- Docker Model Runner
How to use ragbox/bge-reranker with Docker Model Runner:
docker model run hf.co/ragbox/bge-reranker:Q8_0
- Lemonade
How to use ragbox/bge-reranker with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ragbox/bge-reranker:Q8_0
Run and chat with the model
lemonade run user.bge-reranker-Q8_0
List all available models
lemonade list
Update model metadata to set pipeline tag to the new `text-ranking`
Browse filesHello!
## Pull Request overview
* Update metadata to set pipeline tag to the new `text-ranking`
## Changes
This is an automated pull request to update the metadata of the model card. We recently introduced the [`text-ranking`](https://huggingface.co/models?pipeline_tag=text-ranking) pipeline tag for models that are used for ranking tasks, and we have a suspicion that this model is one of them.
Feel free to respond if you have questions or concerns.
- Tom Aarsen